The suppression of immune responses by regulatory T (Treg) cells may play a role in the spreading of viral chronic infectious diseases,1 although their role during HIV infection remains unclear. Treg cells are a subset of T cells involved in the suppression of inflammatory responses and the acquisition of immunologic self-tolerance by preventing the activation of T helper, T-cytotoxic, and B lymphocytes.2-4 Treg cells are characterized by the expression of CD4, CD25High, the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and the glucocorticoid-induced tumor necrosis factor receptor (TNFR) family-related receptor (GITR). FOXP3 is a forkhead transcription factor that induces a regulatory phenotype on transfected non-Treg cells and has become a highly specific marker of Treg cells.5,6
HIV-infected patients show a progressive loss of CD4+ T cells and defects in multiple immune cell types. Functional defects in T cells may be seen even before the decline of the CD4 cell counts and may affect HIV-specific responses.7-10 Whether this selective immunosuppression may be mediated by Treg cells targeting HIV-specific effectors is unknown.11,12 Treg cells may also contribute to limit the unspecific immune activation that leads to the immune dysregulation in HIV-infected patients.13
Controversial reports have been published in the literature on the role and the distribution of Treg cells during HIV infection. Lymphocyte interaction with HIV mainly occurs in lymphoid tissues, especially during active viral replication. Treg cells are more effectively infected by HIV,13 and the Env viral protein promotes Treg differentiation by preventing CD40-CD40L interactions.14 Major efforts have focused on the study of Treg cells in peripheral blood lymphocytes, and thus may not reflect the more relevant events at the active infection sites.11,12,15-18 Moreover, early infection with active viral replication may be a totally different scenario from chronic infection, especially after highly active antiretroviral therapy (HAART). The question of whether the frequency of Treg cells is altered in HIV infection still remains unsolved, mostly because of the poor reproducibility between series.
To clarify the alterations in Treg cells during HIV infection, we analyzed for the first time a unique series of paired tonsil biopsies and peripheral blood samples simultaneously obtained from 27 HIV-infected patients before and after HAART.
MATERIALS AND METHODS
Twenty-seven patients with chronic asymptomatic HIV-1 infection not previously treated with antiretroviral therapy were selected for the study with a mean follow-up of 16 months (range: 11 to 23 months). Clinical features of the patients are shown in Table 1. All patients gave written informed consent to be included in the survey. The study was approved by the local ethics committee. The patients were treated with HAART, defined as a combination of at least 2 nucleoside reverse transcriptase inhibitors and a protease inhibitor (PI) (n = 18) or a nonnucleoside reverse transcriptase inhibitor (NNRTI) (n = 8).
Lymphoid Tissues and Peripheral Blood Samples
Thirty-eight tonsil biopsies were obtained from 27 patients before and after HAART. Fresh tissue was divided in 2 pieces; the first was immediately snap frozen for lymphoid tissue viral load determination and messenger RNA (mRNA) extraction. The second was formalin fixed and paraffin embedded for evaluation of immunoarchitecture and immunohistochemical studies, as previously described.19 All samples had an adequate amount of lymphoid tissue. The series include paired samples before and after HAART from 13 patients. Additional samples, 7 before treatment and 7 after HAART, were obtained from different patients. Six tonsil specimens removed for sleep apnea syndrome in HIV-uninfected patients were used as controls.
Peripheral blood samples were obtained at the time of the biopsy in all cases. Whole blood was collected in ethylenediaminetetraacetic acid (EDTA)-containing tubes. Peripheral blood mononuclear cells (PBMCs) were obtained by separation on Ficoll Hypaque centrifugation gradient. Cells were washed twice in Dulbecco modified Eagle medium (DMEM; BioWhittaker, Walkersville, MD) and fresh analyzed or cryopreserved in 90% fetal calf serum plus 10% dimethylsulfoxide (DMSO, Merck, Darmstadt, Germany) no more than 4 hours after collection.
Lymphoid Tissue and Plasma Viral Load
Lymphoid tissue viral load was determined using the NucliSens HIV-1 RNA QT assay (Organon Teknika, Turnhout, Belgium). RNA was extracted using the Boom extraction method recommended by the manufacturer's protocol (Organon Teknika). For this purpose, 80 sections of 10 μm each were obtained in all cases (mean total weight of 18 mg), and 1 mL of guanidine thiocyanate-containing lysis buffer was added. After homogenization, 1 mL of lysis buffer with RNA internal standards (NucliSens; Organon Teknika) and 50 μL of silica suspension were added to 10 μL of each sample. After centrifugation, the silica pellet was washed 5 times (twice with guanidine thiocyanate-based wash buffer, twice with 70% ethanol, and once with acetone). Subsequently, nucleic acid was eluted using 50 μL of elution buffer (EDTA). A total of 5 μL of this nucleic acid solution in 45 μL of specimen diluent and NASBA (NucliSens) was used. The amount of RNA was expressed as copies per milligram of tissue. The limit of detection of this method for HIV-negative RNA was calculated to be 40 copies/mg of lymphoid tissue.
Plasma viral load was measured using a quantitative polymerase chain reaction (PCR) method (HIV Monitor test Procedure, Amplicor PCR Diagnostic; Hoffman-La Roche, Basel, Switzerland). The amount of RNA was expressed as copies per milliliter with a limit of quantification of 200 copies/mL.
Formalin-fixed paraffin-embedded tissue sections were stained for FOXP3 (clone 236A/E7, 1:10 ratio; Nuffield Department of Clinical Laboratory Sciences, University of Oxford, Headington, Oxford, United Kingdom) in a fully automated platform BondMax (VisionBiosystems, Mount Waverley, Victoria, Australia). We used heat-induced retrieval with ER2 BondMax buffer solution for 10 minutes and detected positivity with a horseradish-peroxidase-linked polymer for 16 minutes (Define; Vision Biosystems) and 5′-3′ diaminobenzidine for 10 minutes as a chromogen.
For dual staining, tissues were stained with antihuman FOXP3 and CD25 (VisionBiosystems), followed by the appropriate fluorescent secondary monoclonal antimouse antibody conjugated with fluorescein isothiocyanate (FITC; FOXP3) or Texas Red (CD25). The slides were washed in phosphate-buffered saline (PBS) for up to 5 minutes, mounted in fluorescence mounting medium (VectaShield; Vector Laboratories, Burlingame, CA) containing 1 μg/mL 4,6-diamidino-2-phenylindole (DAPI) and stored at 4°C until they were examined. The slides were analyzed in an Olympus BX51 microscope (Olympus, Melville, NY), and the images were captured with the Olympus DP70 camera and the DP controller software (Olympus).
Tonsil tissue sections were blindly examined to evaluate the morphologic characteristics of the lymphoid tissue by 3 independent observers (LA, MG, AM) according to a scoring system, as previously described.19
Quantitative Assessment of FOXP3-Positive Treg Cells in Lymphoid Tissues
The number of FOXP3-positive Treg cells was quantified in whole tissue sections in all cases. An automated scanning microscope and image analysis system (Ariol, Applied Imaging SL50; Olympus) were used. Quantification of FOXP3-positive cells was performed with the nuclear Kisight assay (Applied Imaging, Melville, NY) provided by the manufacturer by using a previously described strategy.20 To minimize the heterogeneous distribution of positive cells, a minimum number of 2 complete follicular and interfollicular areas were selected in tonsils classified as stage I (no lymphocyte depletion, prominent germinal centers) or stage II (partial lymphocyte depletion, small follicles). In tonsil biopsies classified as stage III (lymphocyte depletion, no follicles), a minimum of 6 high-power fields (HPFs) were evaluated. In areas in which the images of the nuclei were fused forming a net pattern, shape classes were established in clearly identifiable individual cells, and the settings were applied to the rest of the sample. The mean number of total counted cells per case was 4,409.36 cells. Once areas were selected by the observers, the software collected the data automatically. The observers (JC, AM) were blinded to the clinical data of the patient.
A minimum of 2 × 206 cells/mL in serum-free medium X-VIVO 10 (BioWhitaker) were used. A 3-color flow cytometer FACSCalibur (Becton Dickinson, San Jose, CA) was used. Subpopulations of CD3, CD4, and CD8 cells were determined in all cases by using CD3-peridinin chlorophyll protein (PerCP), CD4-FITC, and CD8-phycoerythrin (PE) (all from Becton Dickinson, Mountain View, CA). Mouse immunoglobulin isotypes conjugated with PerCP, PE, or FITC were always used as negative controls for nonspecific binding. Lymphocytes were gated on the basis of forward and side scatter parameters. A gating region was referred to an FL3/SS (third fluorescence channel vs. side scatter) histogram, where an FL3+ (CD3+) region was defined. This region was further analyzed for the expression of FL1 and FL2. Data were analyzed using CellQuest software (Becton Dickinson, San Diego, CA).
Fluorescent-Activated Cell Sorting Analysis of FOXP3 Expression
Thawed PBMCs (106 per sample) were first surface stained with anti-CD3-PerCP, anti-CD4-antigen-presenting cell (APC), CD45RA-FITC, and/or anti-CD25-FITC. Antibodies to mouse immunoglobulin isotypes conjugated with PerCP, PE, or FITC were always used as negative controls for nonspecific binding (Becton Dickinson, Mountain View, CA); after fixation and permeabilization, cells were incubated with PE-conjugated antihuman FOXP3 antibody (clone 236A/E7; eBioscience, San Diego, CA) or mouse Ig1a isotype control according to the manufacturer's instructions. A minimum of 200,000 cells were examined. Lymphocytes were gated on the basis of forward and side scatter parameters. A gating region was referred to an FL4/FL3 dot plot, where an FL3+FL4+ (CD3+CD4+) region was defined. This region was further analyzed for the expression of FL1 and FL2. For the expression of FOXP3 intracellular staining in CD4+CD25+ or CD4+CD45RA+ T cells, a second gate region (FL4+FL1+) was defined, and FL2 expression was analyzed by an FL1 histogram. Data were analyzed using CellQuest software.
Determination of mRNA Expression of FOXP3 in Tonsil Tissues and Peripheral Blood Cells
Total RNA was extracted from frozen tonsil samples and from cryopreserved PMBCs using RNeasy minikits (Qiagen, Germantown, MA) and the RNAse-Free DNAse Set (Qiagen). RNA was reverse transcribed using the QuantiTect Reverse Transcription Kit (Qiagen). The product was amplified and quantified using complementary DNA (cDNA) TaqMan Universal PCR Master Mix (Applied Biosystems, Foster City, CA) and Assays on Demand for FOXP3 in an ABI Prism 7700 Sequence Detection System (Applied Biosystems). SDS 2.1 software (Applied Biosystems) was used for that purpose. Relative quantification of gene expression was performed as described in the Taqman user's manual using human β-glucuronidase (GUSB; Applied Biosystems) as an internal control.
Wilcoxon signed rank tests were used to analyze the differences between FOXP3 expression in pretreatment and posttreatment samples. A box plot graphic was obtained in each case. Correlation between FOXP3 and viral load was analyzed by using a Pearson linear regression model and Spearman correlation model. All statistical tests were performed with the SPSS v14 statistical software (SPSS, Chicago, IL). The significance level was established at 0.05.
FOXP3 Gene Expression in Lymphoid Tissues
To analyze Treg cells in lymphoid tissue, we studied FOXP3 gene expression by reverse transcriptase (RT) PCR and FOXP3 protein expression by immunohistochemistry in tonsil specimens before and after HAART. We normalized the FOXP3 gene and protein expression to the lymphoid tissue CD4 cell counts.
The pattern of distribution of FOXP3-positive cells was dependent on the architectural stage.19 Stage I, as expected, showed only interfollicular Treg cells. Stages II and III showed a similar distribution to reactive tonsils from HIV-negative individuals. An overall reduction in the proportion of FOXP3-positive Treg cells was observed in HIV-positive patients when compared with HIV-negative individuals (P = 0.018) (Figs. 1A-C, Fig. 2A). The number of FOXP3-positive Treg cells was not correlated with the number of CD25+ cells, and confocal microscopy showed a variable proportion of cells coexpressing these markers (see Figs. 1D-F). After HAART, a reduction (0.5 log) of FOXP3-positive cells was observed (P = 0.012) when compared with untreated patients (before treatment: mean of −1.76 log, range: −2.47 to −0.79 log; after treatment: mean of −2.26 log, range: −3.21 to −1.35 log). No differences in the proportion of FOXP3-positive cells were observed between untreated HIV-positive patients and HIV-negative individuals (see Fig. 2A).
We also analyzed FOXP3 mRNA expression by RT-PCR from the same specimens. As shown in Figure 2B, a marked reduction in FOXP3 expression was observed in HIV-positive patients before (mean of −1.67 log, range: −3.17 to −0.61 log; P = 0.002) and after (mean of −2.28 log, range: −4.1 to −1.04 log; P = 0.001) treatment compared with healthy donors (mean of 1.17 log, range: −1.30 to 2.04 log).
We also observed that FOXP3 protein expression in lymphoid tissues inversely correlated with the number of tissue CD4+ cells in the same specimens (r 2 = 0.32, P < 0.001). Moreover, FOXP3 gene expression was also correlated to CD4 cell counts (r 2 = 0.35, P = 0.001) (Figs. 3A, B).
FOXP3 Gene Expression in Peripheral Blood Mononuclear Cells
We studied FOXP3 gene expression by RT-PCR and protein expression in peripheral blood specimens in CD4+, CD3+, CD25+, or CD45RA+ gates by flow cytometry (Figs. 4A, B). We normalized the FOXP3 gene expression to the peripheral blood CD4 cell counts. In contrast to lymphoid tissue, an overall increase in the proportion of FOXP3-positive cells in peripheral blood was observed in HIV-positive patients compared with healthy donors (mean of −0.65 log, range: −0.92 to −0.4) before (mean of 0.12 log, range: −1.3 to 0.73 log; P = 0.02) and after (mean of 0.12 log, range: −0.24 to 0.42 log; P = 0.002) treatment (see Fig. 4C). Whereas the number of CD4+ cells increased dramatically in almost all cases after HAART (P = 0.005; see Table 1), the proportion of FOXP3 cells was not influenced by treatment (see Fig. 4C). FOXP3 mRNA levels in peripheral blood were influenced only by PI-including regimens (P = 0.019) (before treatment: mean of 0.89 log, range: 0.15 to 1.51 log; after PI treatment: mean of 1.51 log, range: 1.17 to 1.75 log). In a similar way as in flow cytometry, FOXP3 mRNA levels in HIV-positive patients were still higher than in controls (mean of 0.03 log, range: −1.22 to 0.91 log) before (P = 0.018) and after (P = 0.019) treatment (see Fig. 4D).
In contrast to lymphoid tissue, FOXP3 protein and gene expression in peripheral blood did not correlate with the number of CD4+ cells in the same specimens (see Figs. 3C, D).
Interestingly, the number of peripheral blood CD4 cells inversely correlated with the proportion of FOXP3-positive cells in lymphoid tissues, especially in untreated patients (r = −0.692, P = 0.009), suggesting that immunologically recovered patients had a fewer number of tissue FOXP3-expressing cells (data not shown).
Correlation Between FOXP3 Gene Expression in Peripheral Blood and Lymphoid Tissues
In all paired samples, FOXP3 mRNA copy number was higher in peripheral blood than in lymphoid tissues (P = 0.017) in treated and untreated patients. We observed a correlation between FOXP3 mRNA expression in lymphoid tissue and peripheral blood samples before (r = 0.571, P = 0.048) and after (r = −0.867, P = 0.014) treatment. No differences between peripheral blood and lymphoid tissues were found in the control group.
Correlation Between FOXP3 Gene Expression and Viral Replication in Lymphoid Tissues and Peripheral Blood
We analyzed the correlation between viral load and FOXP3 expression in lymphoid tissues and peripheral blood compartments.
Before treatment, all the patients exhibited high viral loads in peripheral blood (29,040.96 copies/mL, range: 200 to 257,626 copies/mL) and lymphoid tissues (1,555,557.72 copies/mg, range: 40 to 8,380,952 copies/mg). After treatment, all patients had reduced viral replication, whereas a reduction of FOXP3 in lymphoid tissue mRNA was observed. mRNA expression and viral load correlated only in peripheral blood in untreated patients (P = 0.035, r 2 = 0.691) and in lymphoid tissues in treated HIV-positive patients (r = −0.54, P = 0.046), although a linear regression was only observed in peripheral blood (Fig. 5). No changes were observed at the protein level (data not shown).
FOXP3 Gene Expression Depends on the Type of Antiretroviral Treatment
In the group of patients in which an NNRTI was used, lower FOXP3 mRNA expression was found compared with the group treated with a PI. This difference occurs in both compartments analyzed, peripheral blood (P = 0.043) and lymphoid tissues (P = 0.028) (see Figs. 2B, 4D).
Intriguingly, these changes were observed in spite of the fact that the number of FOXP3-positive cells was unaltered by morphometry or flow cytometry counts, suggesting that the quantity of mRNA per cell may be lower in patients treated with an NNRTI.
We report, for the first time, the redistribution of Treg cells from lymphoid tissue to the peripheral blood compartment in chronic HIV-infected patients and the impact of the type of HAART by using highly quantitative techniques in 2 different settings: in active HIV replication and in chronic infection after HAART.
Recent reports have shown the relevance of Treg cells in the pathogenesis of HIV infection,11,12,15,16,21-25 with highly controversial results. The lack of reproducibility between series may be attributable in part to the heterogeneity of the cohorts included in the studies: untreated versus treated, untreated versus healthy individuals, or untreated with stable disease versus untreated with progressive disease.11,12,15-18,21-23,26 Moreover, the different methodologic approaches, such as the analysis on different immunologic compartments (PBMCs vs. sorted T-cell populations or lymphoid tissue vs. mucosal sites), the study of different phenotypic Treg markers, and the use of mRNA or protein expression to characterize Treg cells, preclude the comparison between series.
Treg cells are a subset of mostly CD4 cells with suppressive activity of T cells, B cells, and dendritic cells.3,27 The phenotypic characterization of these cells requires a complex combination of multiple cell surface markers, including bright CD25, GITR, and CTLA-4 expression, that impeded the accurate analysis of these cells on tissue sections.
FOXP3 is a definitive marker of mouse Treg differentiation,28 although it is controversial whether the FOXP3 expression alone may be sufficient to define a CD4+ T cell as a Treg cell in humans. FOXP3 expression elicits a suppressive function even in cells with a non-Treg surface phenotype.29 In vitro T-cell receptor (TCR) stimulation of naive T cells from HIV-negative individuals leads to a transforming growth factor-β (TGFβ)-mediated expansion of FOXP3-expressing T cells mostly with suppressive function,30,31 although this may also result in nonregulatory FOXP3-positive T cells.32 In HIV-infected patients, TCR stimulation of naive T cells leads also to a TGFβ-dependent FOXP3 upregulation resulting in Treg cells with in vitro suppressive activity.33 The question of whether or not this mechanism may exist in vivo remains unknown.
We use a highly specific and sensitive antihuman FOXP3 antibody and a Taqman FOXP-3 assay to characterize Treg cell distribution in peripheral blood and lymphoid tissues.20,34 The study of FOXP3 in lymphoid tissues is especially relevant in the pathobiology of HIV infection because there were the active viral replication that occurs. We have shown a redistribution of FOXP3-positive cells in HIV-positive patients, resulting in a substantial reduction in the lymphoid tissues, although an increased number of these cells are observed in the peripheral blood compared with that of HIV-negative individuals. Prior reports also have observed a slight increase in FOXP3 expression in peripheral blood in HIV-infected patients, especially in those with low CD4 cell counts.22,35
Few studies have analyzed the frequency of Treg cells in lymphoid tissues from HIV-infected patients, with controversial results. Prior evidence has shown the accumulation of Treg cells in the lymphoid organs of untreated patients in chronic infection with high suppressive activity compared with peripheral blood.23,25 Moreover, increased FOXP3 mRNA expression has been found in lymph nodes and spleens of early simian immunodeficiency virus (SIV)-infected macaques with high viremia.36 We have observed high FOXP3 expression in the lymphoid tissues of untreated patients with CD4 counts >396 cells/mm3 and high viral loads. This finding is in agreement with prior reports on HIV-positive untreated patients with CD4 counts <488 cells/mm3.15 HAART induced a marked reduction of FOXP3 expression in the lymphoid tissues in our series. The underlying mechanisms are not completely understood and may be multifactorial. In vivo accumulation of Treg cells in lymphoid tissues during early infection may be attributable to the “in situ” differentiation toward induced Treg (TrI) cells of naive CD4+ cells after Env-mediated suppression of CD40L.37 Naturally occurring Treg (nTreg) cells are also important in viral immunity.38 The development of nTreg cells requires the switch from lymph node homing receptors during early development in the thymus to nonlymphoid homing receptor expression during late differentiation in the secondary lymphoid tissues. This switch may contribute to the decrease of Treg cells we observed after HAART. Moreover, FOXP3-positive cells are preferential targets of HIV infection13 especially with the R5-HIV strains that mostly infect CD4+ cells lacking the lymph node homing receptor CD62L,39,40 and only up to 15% of lymphoid tissue CD62L-expressing T cells are infected.40 R5-HIV strains are common in the early phase of the infection, where CD4 counts are >400 cells/mm3, as in our patients. This may explain a preferential depletion of R5-infected Treg cells expressing low levels of CD62L, leading to a relative accumulation of CD62L+ Treg cells with the capacity to migrate to the lymph nodes.41,42 After HAART, viral replication is controlled and may allow to the recovery of the CD62L− peripheral Treg component, contributing to the nodal delocalization of Treg cells,43 and would be consistent with their redistribution from the lymph nodes to peripheral blood. This reduction of lymphoid tissue Treg cells may contribute to the immunologic recovery observed after treatment.
We report for the first time the impact of a particular HAART regimen in this subset of T cells. Our study shows increased FOXP3 gene expression in the group of patients treated with PIs compared with other modalities of HAART. Although the number of cases is limited, this evidence is in agreement with a recent meta-analysis that shows slightly better virologic suppression with NNRTI regimens.44
In summary, HIV-infected patients had low FOXP3 expression in lymphoid tissues and redistributed Treg cells to peripheral blood. HAART induces a reduction of these cells that may contribute to immunologic recovery after controlling viral replication. Finally, the type of HAART given to the patient may differentially affect the distribution of these cells. Treg cell counts may be taken into account in the future to select a specific therapy and/or to monitor the immunologic recovery in HIV-infected patients.
The authors thank Allison Banham (Nuffield Department of Clinical Laboratory Sciences, University of Oxford, Headington, Oxford, United Kingdom) for FOXP3 antibody and her excellent comments.
1. Horohov DW, Moore RN, Rouse BT. Regulation of herpes simplex virus-specific lymphoproliferation by suppressor cells. J Virol
2. Lim HW, Hillsamer P, Kim CH. Regulatory T cells can migrate to follicles upon T cell activation and suppress GC-Th cells and GC-Th cell-driven B cell responses. J Clin Invest
3. Lim HW, Hillsamer P, Banham AH, et al. Cutting edge: direct suppression of B cells by CD4+ CD25+ regulatory T cells. J Immunol
4. Zhao DM, Thornton AM, Dipaolo RJ, et al. Activated CD4+CD25+ T cells selectively kill B lymphocytes. Blood
5. Schubert LA, Jeffery E, Zhang Y, et al. Scurfin (FOXP3) acts as a repressor of transcription and regulates T cell activation. J Biol Chem
6. Hori S, Sakaguchi S. Foxp3: a critical regulator of the development and function of regulatory T cells. Microbes Infect
7. Miedema F, Petit AJ, Terpstra FG, et al. Immunological abnormalities in human immunodeficiency virus (HIV)-infected asymptomatic homosexual men. HIV affects the immune system before CD4+ T helper cell depletion occurs. J Clin Invest
8. Douek DC, Brenchley JM, Betts MR, et al. HIV preferentially infects HIV-specific CD4+ T cells. Nature
9. Plana M, Garcia F, Gallart T, et al. Lack of T-cell proliferative response to HIV-1 antigens after 1 year of highly active antiretroviral treatment in early HIV-1 disease. Immunology Study Group of Spanish EARTH-1 Study. Lancet
10. Plana M, Garcia F, Gallart T, et al. Immunological benefits of antiretroviral therapy in very early stages of asymptomatic chronic HIV-1 infection. AIDS
11. Kinter AL, Hennessey M, Bell A, et al. CD25(+)CD4(+) regulatory T cells from the peripheral blood of asymptomatic HIV-infected individuals regulate CD4(+) and CD8(+) HIV-specific T cell immune responses in vitro and are associated with favorable clinical markers of disease status. J Exp Med
12. Weiss L, Donkova-Petrini V, Caccavelli L, et al. Human immunodeficiency virus-driven expansion of CD4+CD25+ regulatory T cells, which suppress HIV-specific CD4 T-cell responses in HIV-infected patients. Blood
13. Oswald-Richter K, Grill SM, Shariat N, et al. HIV infection of naturally occurring and genetically reprogrammed human regulatory T-cells. PLoS Biol
14. Zhang R, Lifson JD, Chougnet C. Failure of HIV-exposed CD4+ T cells to activate dendritic cells is reversed by restoration of CD40/CD154 interactions. Blood
15. Andersson J, Boasso A, Nilsson J, et al. The prevalence of regulatory T cells in lymphoid tissue is correlated with viral load in HIV-infected patients. J Immunol
16. Apoil PA, Puissant B, Roubinet F, et al. FOXP3 mRNA levels are decreased in peripheral blood CD4+
lymphocytes from HIV-positive patients. J Acquir Immune Defic Syndr
17. Nixon DF, Aandahl EM, Michaelsson J. CD4+CD25+ regulatory T cells in HIV infection. Microbes Infect
18. Tsunemi S, Iwasaki T, Imado T, et al. Relationship of CD4+CD25+ regulatory T cells to immune status in HIV-infected patients. AIDS
19. Alos L, Navarrete P, Morente V, et al. Immunoarchitecture of lymphoid tissue in HIV-infection during antiretroviral therapy correlates with viral persistence. Mod Pathol
20. Carreras J, Lopez-Guillermo A, Fox BC, et al. High numbers of tumor-infiltrating FOXP3-positive regulatory T cells are associated with improved overall survival in follicular lymphoma. Blood
21. Eggena MP, Barugahare B, Jones N, et al. Depletion of regulatory T cells in HIV infection is associated with immune activation. J Immunol
22. Epple HJ, Loddenkemper C, Kunkel D, et al. Mucosal but not peripheral FOXP3+ regulatory T cells are highly increased in untreated HIV infection and normalize after suppressive HAART. Blood
23. Nilsson J, Boasso A, Velilla PA, et al. HIV-1-driven regulatory T-cell accumulation in lymphoid tissues is associated with disease progression in HIV/AIDS. Blood
24. Kinter AL, Horak R, Sion M, et al. CD25+ regulatory T cells isolated from HIV-infected individuals suppress the cytolytic and nonlytic antiviral activity of HIV-specific CD8+ T cells in vitro. AIDS Res Hum Retroviruses
25. Kinter A, McNally J, Riggin L, et al. Suppression of HIV-specific T cell activity by lymph node CD25+ regulatory T cells from HIV-infected individuals. Proc Natl Acad Sci USA
26. Aandahl EM, Michaelsson J, Moretto WJ, et al. Human CD4+ CD25+ regulatory T cells control T-cell responses to human immunodeficiency virus and cytomegalovirus antigens. J Virol
27. Fehervari Z, Sakaguchi S. CD4+ Tregs and immune control. J Clin Invest
28. Hori S, Nomura T, Sakaguchi S. Control of regulatory T cell development by the transcription factor Foxp3. Science
29. Yagi H, Nomura T, Nakamura K, et al. Crucial role of FOXP3 in the development and function of human CD25+CD4+ regulatory T cells. Int Immunol
30. Fantini MC, Becker C, Monteleone G, et al. Cutting edge: TGF-beta induces a regulatory phenotype in CD4+CD25− T cells through Foxp3 induction and down-regulation of Smad7. J Immunol
31. Walker MR, Kasprowicz DJ, Gersuk VH, et al. Induction of FoxP3 and acquisition of T regulatory activity by stimulated human CD4+. J Clin Invest
32. Tran DQ, Ramsey H, Shevach EM. Induction of FOXP3 expression in naive human CD4+FOXP3 T cells by T-cell receptor stimulation is transforming growth factor-β dependent but does not confer a regulatory phenotype. Blood
33. Amarnath S, Dong L, Li J, et al. Endogenous TGF-beta activation by reactive oxygen species is key to Foxp3 induction in TCR-stimulated and HIV-1-infected human CD4+CD25- T cells. Retrovirology
34. Roncador G, Brown PJ, Maestre L, et al. Analysis of FOXP3 protein expression in human CD4+CD25+ regulatory T cells at the single-cell level. Eur J Immunol
35. Montes M, Lewis DE, Sanchez C, et al. Foxp3+ regulatory T cells in antiretroviral-naive HIV patients. AIDS
36. Boasso A, Vaccari M, Hryniewicz A, et al. Regulatory T cell markers, indoleamine (2,3)-dioxygenase and virus levels in spleen and gut during progressive SIV infection. J Virol
. 2007: Aug 22 [Epub ahead of print].
37. Dittmer U, He H, Messer RJ, et al. Functional impairment of CD8(+) T cells by regulatory T cells during persistent retroviral infection. Immunity
38. Rouse BT, Sarangi PP, Suvas S. Regulatory T cells in virus infections. Immunol Rev
39. Gondois-Rey F, Grivel JC, Biancotto A, et al. Segregation of R5 and X4 HIV-1 variants to memory T cell subsets differentially expressing CD62L in ex vivo infected human lymphoid tissue. AIDS
40. Gondois-Rey F, Biancotto A, Fernandez MA, et al. R5 variants of human immunodeficiency virus type 1 preferentially infect CD62L− CD4+ T cells and are potentially resistant to nucleoside reverse transcriptase inhibitors. J Virol
41. Ochando JC, Yopp AC, Yang Y, et al. Lymph node occupancy is required for the peripheral development of alloantigen-specific Foxp3+ regulatory T cells. J Immunol
42. Siegmund K, Feuerer M, Siewert C, et al. Migration matters: regulatory T-cell compartmentalization determines suppressive activity in vivo. Blood
43. Venturi GM, Conway RM, Steeber DA, et al. CD25+CD4+ regulatory T cell migration requires L-selectin expression: L-selectin transcriptional regulation balances constitutive receptor turnover. J Immunol
44. Chou R, Fu R, Huffman LH, et al. Initial highly-active antiretroviral therapy with a protease inhibitor versus a non-nucleoside reverse transcriptase inhibitor: discrepancies between direct and indirect meta-analyses. Lancet
Keywords:© 2007 Lippincott Williams & Wilkins, Inc.
AIDS; FOXP3; HIV; lymphoid tissue; T cells; Treg